What is Softmax function?

Softmax function is an activation function that turns numbers 

into probabilities that sum to one.

Softmax function outputs a vector that represents the probability distributions

of a list of potential outcomes.

In deep learning, This vector represents the last neuron layer of neural network which also

called Logits which are the raw scores output of the neural network.

We will use softmax to map the non-normalized Logits output number of a network to a 

probability distribution over predicted output classes.

e =  2.71828

let's write an example: